Infrared imagery


Background

Infrared cameras on volcanoes

Many of the spectacles of volcanic systems are not limited to the narrow portion of the light spectrum to which our eyes are sensitive. Indeed, oftentimes there is a vast amount of otherwise latent information encoded into the infrared (IR) portion of the light spectrum. Though our eyes are insensitive to IR radiation, we can detect it in the form of heat. Tracking the evolution of temperature—whether of fluids, gases, lava, or simply the ground—in volcanic systems is often an incredibly powerful tool for identifying and diagnosing changes in the subsurface portion of the system.

The last couple of decades has seen a proliferation of low-power infrared cameras with a small enough form factor to be carried and deployed in the field. Provided some calibration has been performed on the cameras, there is a proportional relationship between the brightness of a pixel and the radiative temperature. By capturing a timelapse view of the temperature in the volcanic environment, we can tie this to satellite, and other geophysical, observations to better understand the relationship between heat flux and the eruption cycle at different volcanoes.


AVERT infrared cameras

Our instruments

To capture temperature remotely from hot emitting bodies, thermal detectors are commonly used. These devices measure apparent temperatures that, depending on the way in which they are determined, can be classified as brightness temperatures, colour temperatures, and total radiation temperatures (e.g., Kruse et al., 1962, Bramson, 1968). Brightness temperature is the temperature of a blackbody that would emit the same amount of radiation as the targeted body in a specified spectral band. Colour temperature is defined as the temperature of a blackbody for which the ratio of the spectral radiant emittance at two specified wavelengths is the same as the ratio of the spectral radiant emittance by the targeted body at the same wavelengths. The total radiation temperature corresponds to the temperature at which a blackbody has the same integrated (over the spectrum) radiance as a targeted body.

Example images from the field

The following images show the view of the summit and plume of Cleveland volcano in the infrared spectrum.

An example view of the summit of Cleveland in the infrared spectrum from the CLNE site. The silhouette of Cleveland is present in the foreground, with the plume visible against a dark sky.

The view of the summit and plume of Cleveland in the infrared part of the light spectrum, from the CLNE site.

An example view of the summit of Cleveland in the infrared spectrum from the CLNE site. The silhouette of Cleveland is present in the foreground, with the plume visible against a dark sky.

Another view of the summit and plume of Cleveland in the infrared part of the light spectrum, from the CLNE site.

Data access

Images captured by cameras directed towards our target volcanoes (currently just Cleveland volcano, in the Aleutians) are available for browsing and download through our web archive browser, or can be downloaded via our data API using a command line tool, such as cURL, or the Python requests library. Full documentation of the data API is available here, and an example of how to use request data via the API is shown below:

            
    import requests


    # First, specify our search criteria
    site = "CLNE"
    vnum = 311240
    search_from = "2022-10-01T00:00"
    search_to = "2022-10-02T00:00"

    # Next, construct a database query for images matching these criteria
    base_uri = "https://avert.ldeo.columbia.edu/api/imagery/infrared"
    query = (
        f"{base_uri}/query?"
        f"site={site}&vnum={vnum}"
        f"&search_from={search_from}&search_to={search_to}"
    )

    # Submit these query as a GET request to the data API using requests
    response = requests.get(url=query)

    # If the query returns fewer than 100 results, these can be downloaded
    # as a zipped folder directly
    if len(response.json()) <= 100:
        _ = requests.get(url=f"{query}&download=true")

    # Otherwise, loop over each image and request them from the dedicated
    # single image request API endpoint
    for image in response.json():
        print(f"Downloading image:\n\t{image['image_id']}")
        _ = requests.get(
            url=f"{base_uri}/r/{image['image_id']}&download=true"
        )

            
        

Data attribution

Images from the camera deployed at CLNE are archived at the Lamont-Doherty Earth Observatory, and can be accessed through our web API.